Inventory Routing and Pricing Problem in a Supply Chain Network Design by a Heuristic Method

2017 ◽  
Vol 11 (2) ◽  
pp. 465-470 ◽  
Author(s):  
J. Anix Joel Singh ◽  
M. Saravanan
2020 ◽  
Vol 10 (18) ◽  
pp. 6625
Author(s):  
Farahanim Misni ◽  
Lai Soon Lee ◽  
Hsin-Vonn Seow

This paper considers a location-inventory-routing problem (LIRP) that integrates the strategic, tactical, and operational decision planning in supply chain network design. Both defect and non-defect items of returned products are considered in the cost of reverse logistics based on the economic production quantity model. The objective of the LIRP is to minimize the total cost of location-allocation of established depots, the cost of inventory, including production setup and holding cost, as well as the cost of travelled distance by the vehicles between the open depots and assigned customers. A Hybrid Harmony Search-Simulated Annealing (HS-SA) algorithm is proposed in this paper. This algorithm incorporates the dynamic values of harmony memory considering rate and pitch adjustment rate with the local optimization techniques to hybridize with the idea of probabilistic acceptance rule from simulated annealing, to avoid the local extreme points. Computational experiments on popular benchmark data sets show that the proposed hybrid HS-SA algorithm outperforms a standard HS and an improved HS for all cases.


Author(s):  
Nasrin Mohabbati-Kalejahi ◽  
Alexander Vinel

Hazardous materials (hazmat) storage and transportation pose threats to people’s safety and the environment, which creates a need for governments and local authorities to regulate such shipments. This paper proposes a novel mathematical model for what is termed the hazmat closed-loop supply chain network design problem. The model, which can be viewed as a way to combine several directions previously considered in the literature, includes two echelons in the forward direction (production and distribution centers), three echelons in the backward direction (collection, recovery, and disposal centers), and emergency response team positioning. The two objectives of minimizing the strategic, tactical, and operational costs as well as the risk exposure on road networks are considered in this model. Since the forward flow of hazmat is directly related to the reverse flow, and since hazmat accidents can occur at all stages of the lifecycle (storage, shipment, loading, and unloading, etc.), it is argued that such a unified framework is essential. A robust framework is also presented to hedge the optimization model in case of demand and return uncertainty. The performance of both models is evaluated based on a standard dataset from Albany, NY. Considering the trade-offs between cost and risk, the results demonstrate the design of efficient hazmat closed-loop supply chain networks where the risk exposure can be reduced significantly by employing the proposed models.


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